Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "176"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 176 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 35 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 33 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])]) 

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 176, Node N12:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459850 digital_ok 0.00% 0.00% 0.00% 0.58% 18.02% 0.00% 0.112142 -0.793950 -0.531877 -0.550425 -0.744141 0.012005 -0.231538 1.177992 0.7156 0.7364 0.3733 1.571310 1.337187
2459849 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.311076 -1.333282 0.903225 -0.940802 -1.057707 0.412929 0.932892 6.047691 0.7113 0.7279 0.3770 4.112619 4.125902
2459848 digital_ok 0.00% 0.00% 0.00% 0.00% 30.15% 0.00% 0.019938 -0.927477 -0.667225 1.062761 -0.980853 0.721898 -0.191841 0.774745 0.6849 0.7251 0.3991 1.353896 1.276229
2459847 digital_ok 0.00% 0.00% 0.00% 0.00% 3.21% 0.00% 0.112506 -0.813003 -0.295650 1.269340 -0.460462 0.376908 -0.252259 0.473354 0.6930 0.6551 0.4483 1.452204 1.319766
2459845 digital_ok 0.00% 0.00% 0.00% 0.00% 16.02% 1.66% 0.704930 -0.246480 -0.384592 0.892915 -0.762799 0.045981 -0.030173 1.162628 0.6875 0.7102 0.4036 1.245382 1.245763
2459844 digital_ok 0.00% 100.00% 100.00% 0.00% - - 0.413933 0.799427 -0.880951 1.257057 -0.585882 -1.368157 -0.822268 -1.167015 0.0284 0.0258 0.0015 nan nan
2459843 digital_ok 100.00% 1.20% 0.66% 0.00% 100.00% 0.00% -0.147985 -0.147978 -0.662569 7.155118 -0.715549 9.468118 -0.087289 1.314207 0.7036 0.6905 0.4119 4.474779 3.750483
2459840 digital_ok 100.00% 100.00% 100.00% 0.00% - - 268.305142 212.345338 93.968541 61.669659 1122.260800 829.619845 2240.567094 1745.346277 0.0208 0.0173 0.0015 nan nan
2459839 digital_ok 100.00% - - - - - 43.921364 65.598114 192.364359 219.529336 387.397587 516.084762 2441.405231 4165.788922 nan nan nan nan nan
2459838 digital_ok 0.00% 0.00% 0.00% 0.00% 99.39% 0.61% 0.108678 -0.868400 -0.904010 -0.043431 -0.032051 1.437968 -0.683774 0.158466 0.6515 0.6195 0.4002 0.000000 0.000000
2459836 digital_ok - 100.00% 100.00% 0.00% - - nan nan nan nan nan nan nan nan 0.0345 0.0317 0.0016 nan nan
2459835 digital_ok 0.00% 100.00% 100.00% 0.00% - - 0.251288 0.316854 -0.162538 -0.015552 0.641165 -1.212492 -1.054547 -1.881725 0.0365 0.0316 0.0010 nan nan
2459833 digital_ok 0.00% 100.00% 100.00% 0.00% - - -0.706788 0.672461 -0.595514 -0.730533 -1.288177 -1.786156 -0.681339 -1.473423 0.0349 0.0317 0.0022 nan nan
2459832 digital_ok 0.00% 0.00% 2.69% 0.00% 2.63% 0.00% 0.811136 -0.847920 -1.069357 -0.342776 -0.614230 0.394954 -0.515027 -0.061096 0.7493 0.4321 0.5729 1.619823 1.347814
2459831 digital_ok 0.00% 100.00% 100.00% 0.00% - - -0.289039 0.756456 -0.250774 -0.458538 -1.523768 -1.987317 -0.816392 -1.382628 0.0386 0.0297 0.0018 nan nan
2459830 digital_ok 0.00% 0.00% 0.00% 0.00% 2.63% 0.00% 0.670234 -0.902378 -0.926552 0.239614 0.015795 -0.015795 -0.439446 1.609854 0.7501 0.4462 0.5568 1.608069 1.314350
2459829 digital_ok 0.00% 0.00% 0.00% 0.00% 0.65% 99.35% 1.049615 -0.460621 -0.909602 0.223768 -0.493882 0.513220 -0.010411 3.177897 0.6747 0.5817 0.4116 6.713401 28.812654
2459828 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.700245 -0.884160 -0.763922 -0.051525 0.432563 0.517416 0.858279 9.661708 0.7452 0.4494 0.5388 0.000000 0.000000
2459827 digital_ok 0.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.505548 -0.297552 -0.364924 1.094200 -0.718478 0.252076 -0.064967 1.591698 0.0569 0.0728 0.0049 15.351949 41.057445
2459826 digital_ok 0.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.621108 -0.446415 -0.460702 0.821804 -0.120189 0.666029 -0.376210 1.952170 0.0428 0.0684 0.0055 18.669294 18.911151
2459825 digital_ok 0.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.053400 -0.970229 -0.993976 0.039915 0.017221 0.218181 -0.333459 0.758886 0.0426 0.0618 0.0041 0.000000 0.000000
2459824 digital_ok 0.00% 100.00% 100.00% 0.00% 100.00% 0.00% 1.125205 -0.063646 -0.906707 0.095574 -0.980206 1.064147 -0.191677 0.087345 0.0669 0.0726 0.0071 7.701315 22.045517
2459823 digital_ok 0.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.283350 -0.017149 -0.313364 0.999755 0.159393 0.517547 -0.258183 3.981721 0.0528 0.0648 0.0077 219.337532 100.126732
2459822 digital_ok 0.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.152784 -0.788094 -0.494150 0.637869 0.049549 -0.002923 -0.042345 -0.036795 0.0526 0.0686 0.0107 1.236582 1.237240
2459821 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 364.940315 365.150607 inf inf 726.073916 919.716499 1095.723916 1326.666179 nan nan nan 0.000000 0.000000
2459820 digital_ok 0.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.455195 -0.665599 -0.376955 0.902056 -0.055985 1.675831 -0.694271 -0.606118 0.0570 0.0667 0.0078 0.887608 0.886776
2459817 digital_ok 0.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.224189 -0.852810 -0.636670 0.537542 -0.782006 -0.828412 -0.603303 -0.698305 0.0555 0.0662 0.0076 1.237482 1.231811
2459816 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.718341 -0.498855 -1.096652 -0.075920 -0.755124 -0.871004 -0.327792 -0.997452 0.8456 0.5479 0.6318 1.828548 1.445884
2459815 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% -0.089380 -0.674291 -1.026684 0.373720 -0.155130 -0.097269 -0.661615 -0.647945 0.7880 0.6177 0.5498 1.688523 1.327031
2459814 digital_ok 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 176: 2459850

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Temporal Discontinuties 1.177992 0.112142 -0.793950 -0.531877 -0.550425 -0.744141 0.012005 -0.231538 1.177992

Antenna 176: 2459849

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Temporal Discontinuties 6.047691 0.311076 -1.333282 0.903225 -0.940802 -1.057707 0.412929 0.932892 6.047691

Antenna 176: 2459848

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Power 1.062761 -0.927477 0.019938 1.062761 -0.667225 0.721898 -0.980853 0.774745 -0.191841

Antenna 176: 2459847

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Power 1.269340 -0.813003 0.112506 1.269340 -0.295650 0.376908 -0.460462 0.473354 -0.252259

Antenna 176: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Temporal Discontinuties 1.162628 -0.246480 0.704930 0.892915 -0.384592 0.045981 -0.762799 1.162628 -0.030173

Antenna 176: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Power 1.257057 0.413933 0.799427 -0.880951 1.257057 -0.585882 -1.368157 -0.822268 -1.167015

Antenna 176: 2459843

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Temporal Variability 9.468118 -0.147978 -0.147985 7.155118 -0.662569 9.468118 -0.715549 1.314207 -0.087289

Antenna 176: 2459840

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
176 N12 digital_ok ee Temporal Discontinuties 2240.567094 268.305142 212.345338 93.968541 61.669659 1122.260800 829.619845 2240.567094 1745.346277

Antenna 176: 2459839

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Temporal Discontinuties 4165.788922 65.598114 43.921364 219.529336 192.364359 516.084762 387.397587 4165.788922 2441.405231

Antenna 176: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Temporal Variability 1.437968 -0.868400 0.108678 -0.043431 -0.904010 1.437968 -0.032051 0.158466 -0.683774

Antenna 176: 2459835

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok ee Temporal Variability 0.641165 0.316854 0.251288 -0.015552 -0.162538 -1.212492 0.641165 -1.881725 -1.054547

Antenna 176: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Shape 0.672461 0.672461 -0.706788 -0.730533 -0.595514 -1.786156 -1.288177 -1.473423 -0.681339

Antenna 176: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
176 N12 digital_ok ee Shape 0.811136 0.811136 -0.847920 -1.069357 -0.342776 -0.614230 0.394954 -0.515027 -0.061096

Antenna 176: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Shape 0.756456 -0.289039 0.756456 -0.250774 -0.458538 -1.523768 -1.987317 -0.816392 -1.382628

Antenna 176: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Temporal Discontinuties 1.609854 0.670234 -0.902378 -0.926552 0.239614 0.015795 -0.015795 -0.439446 1.609854

Antenna 176: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Temporal Discontinuties 3.177897 -0.460621 1.049615 0.223768 -0.909602 0.513220 -0.493882 3.177897 -0.010411

Antenna 176: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Temporal Discontinuties 9.661708 -0.884160 0.700245 -0.051525 -0.763922 0.517416 0.432563 9.661708 0.858279

Antenna 176: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Temporal Discontinuties 1.591698 0.505548 -0.297552 -0.364924 1.094200 -0.718478 0.252076 -0.064967 1.591698

Antenna 176: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Temporal Discontinuties 1.952170 -0.446415 0.621108 0.821804 -0.460702 0.666029 -0.120189 1.952170 -0.376210

Antenna 176: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Temporal Discontinuties 0.758886 -0.970229 -0.053400 0.039915 -0.993976 0.218181 0.017221 0.758886 -0.333459

Antenna 176: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
176 N12 digital_ok ee Shape 1.125205 1.125205 -0.063646 -0.906707 0.095574 -0.980206 1.064147 -0.191677 0.087345

Antenna 176: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Temporal Discontinuties 3.981721 -0.017149 -0.283350 0.999755 -0.313364 0.517547 0.159393 3.981721 -0.258183

Antenna 176: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Power 0.637869 -0.152784 -0.788094 -0.494150 0.637869 0.049549 -0.002923 -0.042345 -0.036795

Antenna 176: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Power inf 365.150607 364.940315 inf inf 919.716499 726.073916 1326.666179 1095.723916

Antenna 176: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Temporal Variability 1.675831 0.455195 -0.665599 -0.376955 0.902056 -0.055985 1.675831 -0.694271 -0.606118

Antenna 176: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Power 0.537542 -0.224189 -0.852810 -0.636670 0.537542 -0.782006 -0.828412 -0.603303 -0.698305

Antenna 176: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok ee Shape 0.718341 -0.498855 0.718341 -0.075920 -1.096652 -0.871004 -0.755124 -0.997452 -0.327792

Antenna 176: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Power 0.373720 -0.674291 -0.089380 0.373720 -1.026684 -0.097269 -0.155130 -0.647945 -0.661615

Antenna 176: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 176: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
176 N12 digital_ok nn Shape nan nan nan inf inf nan nan nan nan

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